Vehicles Lit HeadLights Detection API

Vehicles Lit HeadLights Detection API - LightsLitDet (also known as LightsLit Detection API or Auto LightsLit Detection API) is a cross browsers REST API which get a JSON input with a still photo (as base64 encoded string), containing vehicles with headlights lit or unlit, front view and returns a JSON string which contains a base64 encoded string photo with rectangles drawn over Lit HeadLights of a vehicle, confidence score, timestamp, vertices for bounding boxes of Vehicles Lit HeadLights. Of course, there are some limitations in order to get a higher accuracy. We recommend properly exposed, unobstructed JPEG photos at 1920x1080 (full HD resolution) where the lit headlights are clear and focused. If the lit headlights are too small or blured, the accuracy is lower and the AI algorithm may not see the lit headlights. The lit headlights must be focalized, unobstructed, with details very clear. We do not store pictures. Also, the quality and the angles of the camera are very important and it contribute to a higher reading accuracy. It should have varifocal lenses, high shutter speed, good infrared lighting beam, full HD resolution.

Allthough this Automatic Vehicles Lit HeadLights Detection API (currently we do not offer a Vehicles Lit HeadLights Detection sdk) is intended for software development and therefore developers, we have also here an Vehicles Lit HeadLights Detection online application that may be used to check the input and output JSONs of the API. The necessary steps are written below, basically for this real time Vehicles Lit HeadLights Detection API you send an authorized POST request in JSON format to the API endpoint and you get as JSON response the output as described below through parameters and examples.

This Vehicles Lit HeadLights Detection API is useful for a large number of domains like apps for detecting: LightsLit for cars, SUVs, trucks, tractors, vans, buses, motorcycles, ATVs etc. You own the commercial copyright of the resulted JSON with no additional fee meaning you may use it in your own apps for sale.

For using our Vehicles Lit HeadLights Detection API and/or APP you must create an account (free of charge, no card required), activate it from your received email, login and then start your TRIAL package with no fees as you can see at our pricing packages. After you have tested the API and/or APP and you are satisfied, you may buy a paid package. You will always see at your Admin Console page the real resources consumption in real time, your invoices, you may see/edit/delete your profile or export log consents as GDPR instructed, you may read our FAQs.

Vehicles Lit HeadLights Detection APP

Photo File
Image URL(*)
* Let the "NO" value of Image URL if you upload a Photo File, otherwise write the image url like http://domainname.com/image.jpg



API Endpoint (method POST):
https://gatiosoft.ro/lightslitdet.aspx
Headers:
Authorization: Basic //Your username:password are base64 encoded string
Content-Type: application/json
Accept: application/json
JSON Request Body (change inputs here and see in real time below):
                   {
  "base64_Photo_String": "iVBORw0KGgoAAAA...base64 encoded string photo...GAAAAAElFTkSuQmCC",
  "photo_url": "NO"
}
               
JSON Response From API (change inputs here and see in real time below):
{
  "created": "2020-05-02T12:28:09.989Z",
  "predictions": [
    {
      "probability": 0.4453594,
      "tagId": "6b333d95-e461-4155-890c-9921158f7d17",
      "tagName": "Lit HeadLights",
      "boundingBox": {
        "left": 0.590857267,
        "top": 0.049960345,
        "width": 0.153553188,
        "height": 0.287757039
      },
      "boundingBoxPhoto": ""
    },
    {
      "probability": 0.6109611,
      "tagId": "6b333d95-e461-4155-890c-9921158f7d17",
      "tagName": "Lit HeadLights",
      "boundingBox": {
        "left": 0.241624564,
        "top": 0.2652982,
        "width": 0.137271315,
        "height": 0.2830975
      },
      "boundingBoxPhoto": ""
    }
  ],
  "final_photo": "iRRfdewqRA..final base64 encoded string photo with drawn bounding boxes...SwervasCC"
}
JSON Response (Example) From API in case of ERROR:

 [
  {
    "cd": "1001",
    "description": "The authorization header Is either empty Or isn't Basic"
  }
]

Request Parameters Table

Parameter Name
Parameter Description
base64_Photo_String
This is the input photo as base64 encoded string[string] from which will be detected and cropped Vehicles Lit HeadLights bounding boxes.
photo_url
This is the image url [string] used for the input photo. Its default value is NO because the above parameter base64_Photo_String is set. If this parameter is set to an image url, base64_Photo_String value must be NO.

Response Parameter Table

Parameter Name
Parameter Description
created  
This is the timestamp as  [string] at the moment that request is made.
final_photo 
This is the final photo base64 encoded string [string] upon which bounding boxes are drawn.
predictions
This is a list or array which contains the parameters explained below.
probability
This is the probability score [real] of the detected Vehicles Lit HeadLights.
tagId
This is the tagId [string] for the detected Vehicles Lit HeadLights. Example: 6b333d95-e461-4155-890c-9921158f7d17.
tagName
This is the tagName [string] for the detected Vehicles Lit HeadLights. Example of tagName: Vehicles Lit HeadLights.
boundingBox
This is an object that contains the below explained parameters.
left
This is the upper left coordinate [real] of the rectangular bounding box surrounding the detected Vehicles Lit HeadLights.
top
This is the upper top coordinate [real] of the rectangular bounding box surrounding the detected Vehicles Lit HeadLights.
width
This is the width [real] of the rectangular bounding box surrounding the detected Vehicles Lit HeadLights.
height
This is the height [real] of the rectangular bounding box surrounding the detected Vehicles Lit HeadLights.

Response Error Codes Table

Parameter Name
Parameter Description
cd

This is the error code which may be:

  • 1001
  • 1002
  • 1003
  • 1004
  • 1005
  • 1006
  • 1007
  • 1008
  • 1009
  • 1010
  • 1011
  • 1012
  • 1013
  • 1014
  • 1015
  • 1016
  • 2001
description

This is the description of the error code which may be:

  • 1001 - The authorization header is either empty or isn't Basic.
  • 1002 - Daily requests number exceeded in TRIAL mode!
  • 1003 - Trial expired!
  • 1004 - Requests number exceeded!
  • 1005 - Package expired!
  • 1006 - No invoice!
  • 1007 - Reader is NULL for TRIAL!
  • 1008 - Cannot Read if TRIAL exists!
  • 1009 - Error connecting to database looking for TRIAL! (and a detailed description message of the encountered error)
  • 1010 - Reader is NULL for Invoice!
  • 1011 - Cannot Read if Invoice exists!
  • 1012 - Error connecting to database! (and a detailed description message of the encountered error)
  • 1013 - Input request too long! Maximum 5 MB per request are allowed / Nothing to upload
  • 1014 - Invalid request data! (and a detailed description message of the encountered error)
  • 2001 - Invalid request data after passing to the API (and a detailed description message of the encountered error)

Source Code Examples for Using Our Vehicles Lit HeadLights Detection API

                       
Imports System
Imports System.Text
imports System.Collections.Generic
Imports System.Net
Imports Newtonsoft.Json

Public Class vehicles_lit_headlights_detection_api
    Public Class ResponseFields
	 Public Property created As String
         Public Property predictions As New List(Of prediction)
         Public Property final_photo As String
    End Class

    Public Class prediction
	 Public Property probability As Single
         Public Property tagId As String
         Public Property tagName As String
         Public Property boundingBox As New boundingbox
         Public Property boundingBoxPhoto As String
    End Class

    Public Class boundingbox
	 Public Property left As Single
         Public Property top As Single
         Public Property width As Single
         Public Property height As Single
    End Class
    
    Public Class ErrorFields
        Public Property cd As String
        Public Property description As String
    End Class

    Protected Sub SendRequest()
        Dim Client As WebClient = New WebClient()
        Dim credentials As String = Convert.ToBase64String(Encoding.ASCII.GetBytes("your_username:your_password"))
        Client.Headers(HttpRequestHeader.Authorization) = String.Format("Basic {0}", credentials)
        Client.Headers(HttpRequestHeader.Accept) = "application/json"
        Client.Headers(HttpRequestHeader.ContentType) = "application/json"
	Client.BaseAddress = "https://gatiosoft.ro/LightsLitdet.aspx"
        Dim resString As String = ""

        Try
            Dim js As String = "Replace this string with your JSON Request Body string like in the example above on the website"
            Dim reqString As Byte() = Encoding.UTF8.GetBytes(js)
            Dim url As Uri = New Uri(Client.BaseAddress)
            Dim resByte As Byte() = Client.UploadData(url, "post", reqString)
            resString = Encoding.UTF8.GetString(resByte)

	    If resString.IndexOf("predictions") > 0 Then
                Dim r As ResponseFields = New ResponseFields()
                r = JsonConvert.DeserializeObject(Of ResponseFields)(resString)
                Console.Write(resString)
            Else
		Dim e As list(of ErrorFields) = New list(of ErrorFields)
		e = JsonConvert.DeserializeObject(Of list(of ErrorFields))(resString)
                Console.Write(e(0).cd)
                Console.Write(e(0).description)
            End If

            Client.Dispose()
        Catch exception As Exception
            Dim ex As System.Exception = exception
            Console.Write("ERROR: " & resString & ex.Message)
        End Try
    End Sub

    Public Shared Sub Main()
	Dim b As vehicles_lit_headlights_detection_api = New  vehicles_lit_headlights_detection_api
        b.SendRequest()
    End Sub
End Class



LightsLitDet Online Video Presentation

Vehicles Lit HeadLights Detection API, LightsLitdet is in the video presentation below. There are several search terms which you may use like: Vehicles Lit HeadLights Detection sdk, Vehicles Lit HeadLights Detection c#, Vehicles Lit HeadLights Detection online, LightsLit for autos detection api, automatic Vehicles Lit HeadLights Detection, Vehicles Lit HeadLights Detection python, Vehicles Lit HeadLights Detection python, real time Vehicles Lit HeadLights Detection python, python Vehicles Lit HeadLights Recognition, image processing Vehicles Lit HeadLights Detection.

 



Pricing Packages

Please choose one of the below pricing packages for start using our Vehicles Lit HeadLights Detection API and online APP!

Start TRIAL
No catches

  • 7 days TRIAL
  • Use our cloud REST API and online APP
  • Maximum 50 requests per DAY in trial period
  • You do NOT own the commercial copyright for using the API in your apps in trial period.
  • Get Vehicles Lit HeadLights tagID and Name if detected in one photo.
  • Get bounding boxes vertices for each Vehicles Lit HeadLights detected in one photo.
  • Get confidence score for bounding boxes
  • Unlimited Devices
  • Administration console
  • Support through online chat and/or tickets
  • We do NOT allow spam accounts for TRIAL



Monthly TIER
Popular

  • 80 USD per month
  • Use our cloud REST API and online APP
  • Maximum 10000 predictions(*) per month
  • Maximum 50 requests per MINUTE
  • You own the commercial copyright to use it in your apps.
  • Get Vehicles Lit HeadLights tagID and Name if detected in one photo.
  • Get bounding boxes vertices for each Vehicles Lit HeadLights detected in one photo.
  • Get confidence score for bounding boxes
  • Unlimited Devices
  • Administration console
  • Premium support through online chat and/or tickets, very supportive help and quick responses.



Yearly TIER
(15% Discount)

  • 816 USD per year
  • Use our cloud REST API and online APP
  • Maximum 10000 predictions(*) per month
  • Maximum 50 requests per MINUTE
  • You own the commercial copyright to use it in your apps.
  • Get Vehicles Lit HeadLights tagID and Name if detected in one photo.
  • Get bounding boxes vertices for each Vehicles Lit HeadLights detected in one photo.
  • Get confidence score for bounding boxes
  • Unlimited Devices
  • Administration console
  • Premium support through online chat and/or tickets, very supportive help and quick responses.



Note: VAT rate may be added or not, function to your country and/or if you are a taxable person or company.
* Prediction - on the input photo may exist many predictions, each of it with certain amount of probability of detected Vehicles Lit HeadLights on the photo. Even we filter the output predictions to those with probability score greater than 20%, for the input photo all predictions are counted.